Triple
T8849389
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pierre Sermanet |
E210596
|
entity |
| Predicate | coAuthorWith |
P398
|
FINISHED |
| Object | Andrew Rabinovich |
E224264
|
NE FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Andrew Rabinovich | Statement: [Pierre Sermanet, coAuthorWith, Andrew Rabinovich]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Andrew Rabinovich Context triple: [Pierre Sermanet, coAuthorWith, Andrew Rabinovich]
-
A.
Andrew Rabinovich
chosen
Andrew Rabinovich is a computer scientist and researcher known for his contributions to computer vision and deep learning, including influential work at Google.
-
B.
Jack Rabinovitch
Jack Rabinovitch was a Canadian businessman and philanthropist best known for creating one of Canada’s most prestigious literary awards, the Giller Prize.
-
C.
Jay Rabinowitz
Jay Rabinowitz is a film editor known for his work on numerous feature films, including the science-fiction thriller "The Adjustment Bureau."
-
D.
Eric Tannenbaum
Eric Tannenbaum is a television producer best known for his work on popular American sitcoms, including serving as an executive producer on "Two and a Half Men."
-
E.
Michael Aronov
Michael Aronov is an American actor known for his work in film, television, and theater, including a role in the historical drama "Operation Finale."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69ca838a424c8190b1ecac115c2927e7 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc60abb0748190af41d4e1f419e39c |
completed | April 1, 2026, 12:02 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1cc2600208190b996bac5845bd385 |
completed | April 5, 2026, 2:42 a.m. |
Created at: March 30, 2026, 6:49 p.m.